data<-read.table("normal.out")
data<-as.vector(data[,1])
data1<-data[data<101]
pdf("hist_normal.pdf")
h1<-hist(as.numeric(data),breaks=seq(2,110,0.01),plot=FALSE)
h1$counts <-rev(cumsum(rev(h1$counts)))
plot(h1,xlab="quality Scores",ylab ="counts",main="histogram_quality_scores_normal",xlim=c(0,110),ylim=c(0,100000000))
dev.off()
pdf("hist_normal_removed110.pdf")
h1<-hist(as.numeric(data1),breaks=seq(2,100,0.01),plot=FALSE)
h1$counts <-rev(cumsum(rev(h1$counts)))
plot(h1,xlab="quality Scores",ylab ="counts",main="histogram_quality_scores_normal",xlim=c(0,100),ylim=c(0,44000000))
dev.off()

data2<-read.table("tumor.out")
data2<-as.vector(data2[,1])
data21<-data2[data2<101]
pdf("hist_tumor.pdf")
h12<-hist(as.numeric(data2),breaks=seq(2,110,0.01),plot=FALSE)
h12$counts <-rev(cumsum(rev(h12$counts)))
plot(h12,xlab="quality Scores",ylab ="counts",main="histogram_quality_scores_normal",xlim=c(0,110),ylim=c(0,100000000))
dev.off()
pdf("hist_tumor_removed110.pdf")
h12<-hist(as.numeric(data21),breaks=seq(2,100,0.01),plot=FALSE)
h12$counts <-rev(cumsum(rev(h12$counts)))
plot(h12,xlab="quality Scores",ylab ="counts",main="histogram_quality_scores_normal",xlim=c(0,100),ylim=c(0,44000000))
dev.off()
